Abstract: Briefly, embodiments disclosed herein relate generally to on-line content sampling, and more particularly to utilization of machine learning techniques to sample on-line content in a search engine environment, for example.

Abstract: Techniques for using machine learning models to approximate a user in a communication are described. For example, a method of initiating a communication link with an edge device to exchange audio data; receiving a compressed audio data from the edge device; re-encoding the received compressed audio data using a re-encoding machine learning model to approximate a voice; and outputting the approximated voice is detailed.

Abstract: Systems and methods for identifying which video segment is being displayed on a screen of a television system. The video segment is identified by deriving data from the television signals, the derived data being indicative of the video segment being displayed on file screen. This feature can be used to extract a viewer's reaction (such as changing the channel) to a specific video segment (such as an advertisement) and reporting the extracted information as metrics. The systems and methods may further provide contextually targeted content to the television system. The contextual targeting is based on not only identification of the video segment being displayed, but also a determination concerning the playing time or offset time of the particular portion of the video segment being currently displayed.

Abstract: In an aspect, fantasy sports data is analyzed to generate and/or manage the delivery of and user experience of fantasy sports games and contests, including timing and payout structure(s) for short-term fantasy contests, such as daily, weekly, etc. fantasy sports contests, that motivate and appeal to contestants and is/are reasonably structured and concisely represented. In yet another aspect, a daily fantasy contest system is provided to automatically adjust to user demand without overshooting profitable levels and offer a variety of different contests, as well as offer contests with guaranteed and non-guaranteed payouts.

Abstract: In an aspect, fantasy sports data is analyzed to generate and/or manage the delivery of and user experience of fantasy sports games and contests, including timing and payout structure(s) for short-term fantasy contests, such as daily, weekly, etc. fantasy sports contests, that motivate and appeal to contestants and is/are reasonably structured and concisely represented. In yet another aspect, a daily fantasy contest system is provided to automatically adjust to user demand without overshooting profitable levels and offer a variety of different contests, as well as offer contests with guaranteed and non-guaranteed payouts.

Abstract: Techniques for auto-scaling hosted machine learning models for production inference are described. A machine learning model can be deployed in a hosted environment such that the infrastructure supporting the machine learning model scales dynamically with demand so that performance is not impacted. The model can be auto-scaled using reactive techniques or predictive techniques.

Abstract: Disclosure includes an electronic message composition support system, method and architecture. Techniques including machine learning and natural language processing techniques are used to extend message composition capability and support and to provide feedback to a user regarding an error, condition, etc. detected in the user's message before the user sends the message, e.g., while the user is composing the message using a messaging application's user interface.

Abstract: Techniques for dynamic accuracy-based experimentation and deployment of machine learning (ML) models are described. Inference traffic flowing to ML models and the accuracy of the models is analyzed and used to ensure that better performing models are executed more often via model selection. A predictive component can evaluate which model is more likely to be accurate for certain input data elements. Ensemble techniques can combine inference results of multiple ML models to aim to achieve a better overall result than any individual model could on its own.

Abstract: Systems and methods for identifying which video segment is being displayed on a screen of a television system. The video segment is identified by deriving data from the television signals, the derived data being indicative of the video segment being displayed on file screen. This feature can be used to extract a viewer's reaction (such as changing the channel) to a specific video segment (such as an advertisement) and reporting the extracted information as metrics. The systems and methods may further provide contextually targeted content to the television system. The contextual targeting is based on not only identification of the video segment being displayed, but also a determination concerning the playing time or offset time of the particular portion of the video segment being currently displayed.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content providing, generating and/or hosting systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the security and quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide added security features and functionality to messaging platforms.

Abstract: In an aspect, fantasy sports data is analyzed to generate and/or manage the delivery of and user experience of fantasy sports games and contests, including timing and payout structure(s) for short-term fantasy contests, such as daily, weekly, etc. fantasy sports contests, that motivate and appeal to contestants and is/are reasonably structured and concisely represented. In yet another aspect, a daily fantasy contest system is provided to automatically adjust to user demand without overshooting profitable levels and offer a variety of different contests, as well as offer contests with guaranteed and non-guaranteed payouts.

Abstract: An electronic message composition support system, method and architecture is provided. Techniques including machine learning and natural language processing techniques are used to extend message composition capability and support and to provide feedback to a user regarding an error, condition, etc. detected in the user's message before the user sends the message, e.g., while the user is composing the message using a messaging application's user interface.

Abstract: Techniques for accent translation are described herein. A plurality of audio samples may be received, and each of the plurality of audio samples may be associated with at least one of a plurality of accents. Audio samples associated with at least a first accent of the plurality of accents may be compared to audio samples associated with at least one other accent of the plurality of accents. A translation model between the first accent and a second accent may be generated. An input audio portion in a first spoken language may be received. It may be determined whether the input audio portion is substantially associated with the first accent, and if so, an output audio portion substantially associated with the second accent in the first spoken language may be outputted based, at least in part, on the translation model.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content providing, generating and/or hosting systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the security and quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide added security features and functionality to messaging platforms.

Abstract: Techniques for accent translation are described herein. A plurality of audio samples may be received, and each of the plurality of audio samples may be associated with at least one of a plurality of accents. Audio samples associated with at least a first accent of the plurality of accents may be compared to audio samples associated with at least one other accent of the plurality of accents. A translation model between the first accent and a second accent may be generated. An input audio portion in a first spoken language may be received. It may be determined whether the input audio portion is substantially associated with the first accent, and if so, an output audio portion substantially associated with the second accent in the first spoken language may be outputted based, at least in part, on the translation model.

Abstract: Systems and methods for identifying which video segment is being displayed on a screen of a television system. The video segment is identified by deriving data from the television signals, the derived data being indicative of the video segment being displayed on file screen. This feature can be used to extract a viewer's reaction (such as changing the channel) to a specific video segment (such as an advertisement) and reporting the extracted information as metrics. The systems and methods may further provide contextually targeted content to the television system. The contextual targeting is based on not only identification of the video segment being displayed, but also a determination concerning the playing time or offset time of the particular portion of the video segment being currently displayed.

Abstract: Systems and methods for identifying which video segment is being displayed on a screen of a television system. The video segment is identified by deriving date from the television signals, the derived data being indicative of the video segment being displayed on file screen. This feature can be used to extract a viewer's reaction (such as changing the channel) to a specific video segment (such as an advertisement) and reporting the extracted information as metrics. The systems and methods may further provide contextually targeted content to the television system. The contextual targeting is based on not only identification of the video segment being displayed, hut also a determination concerning the playing time or offset time of the particular portion of the video segment being currently displayed.

Abstract: Disclosure includes an electronic message composition support system, method and architecture. Techniques including machine learning and natural language processing techniques are used to extend message composition capability and support and to provide feedback to a user regarding an error, condition, etc. detected in the user's message before the user sends the message, e.g., while the user is composing the message using a messaging application's user interface.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content providing, generating and/or hosting systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the security and quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide added security features and functionality to messaging platforms.

Abstract: Briefly, embodiments disclosed herein relate generally to on-line content sampling, and more particularly to utilization of machine learning techniques to sample on-line content in a search engine environment, for example.